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https://github.com/tkoyama010/awesome-python-data-visualization

😎 list of awesome python data visualization
https://github.com/tkoyama010/awesome-python-data-visualization

List: awesome-python-data-visualization

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😎 list of awesome python data visualization

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# Awesome Python Data Visualization [![Awesome](https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)](https://github.com/sindresorhus/awesome)



[](https://pyviz.org/)



> Useful Python tools for data visualizations Python frameworks, libraries, and software of Data Visualization



This list is a collection of tools, projects, images, and resources conforming to the [Awesome Manifesto](https://github.com/sindresorhus/awesome/blob/main/awesome.md)



Contributions _very welcome_ but first see [Contributing](CONTRIBUTING.md).



## Table of Contents



- [Core](#core)

- [High-Level Shared API](#high-level-shared-api)

- [High-Level](#high-level)

- [Native-GUI](#native-gui)

- [Other InfoVis](#other-infovis)

- [SciVis](#scivis)

- [Geospatial](#geospatial)

- [Graphs and networks](#graphs-and-networks)

- [Other domain-specific](#other-domain-specific)

- [Large-data rendering](#large-data-rendering)

- [Dashboarding](#dashboarding)

- [Colormapping](#colormapping)

- [Not in PyViz](#not-in-pyviz)



## Core



**[`^        back to top        ^`](#table-of-contents)**



- [matplotlib](https://matplotlib.org/) - 2D plotting library.

- [plotly](https://plot.ly/python/) - Interactive web based visualization built on top of [plotly.js](https://github.com/plotly/plotly.js)

- [bokeh](https://bokeh.pydata.org/en/latest/) - Interactive Web Plotting for Python.



## High-Level Shared API



**[`^        back to top        ^`](#table-of-contents)**



## High-Level



**[`^        back to top        ^`](#table-of-contents)**



- [altair](https://altair-viz.github.io/) - Declarative statistical visualizations, based on Vega-Lite.

- [seaborn](https://seaborn.pydata.org/) - A library for making attractive and informative statistical graphics.

- [Chartify](https://github.com/spotify/chartify) - Bokeh wrapper that makes it easy for data scientists to create charts.

- [holoviews](https://holoviews.org/) - Complex and declarative visualizations from annotated data.



## Native-GUI



**[`^        back to top        ^`](#table-of-contents)**



- [PyQtGraph](https://www.pyqtgraph.org/) - Interactive and realtime 2D/3D/Image plotting and science/engineering widgets.



## Other InfoVis



**[`^        back to top        ^`](#table-of-contents)**



- [bqplot](https://github.com/bloomberg/bqplot) - Interactive Plotting Library for the Jupyter Notebook.

- [plotnine](https://github.com/has2k1/plotnine) - A grammar of graphics for Python based on ggplot2.

- [pygal](http://www.pygal.org/en/latest/) - A Python SVG Charts Creator.

- [toyplot](https://toyplot.readthedocs.io/en/stable/) - The kid-sized plotting toolkit for Python with grownup-sized goals.



## SciVis



**[`^        back to top        ^`](#table-of-contents)**



- [glumpy](https://github.com/glumpy/glumpy) - OpenGL scientific visualizations library.

- [mayavi](https://docs.enthought.com/mayavi/mayavi/) - interactive scientific data visualization and 3D plotting in Python.

- [PyVista](https://github.com/pyvista/pyvista) – 3D plotting and mesh analysis through a streamlined interface for the Visualization Toolkit (VTK)

- [vedo](https://vedo.embl.es) - Library for scientific analysis and visualization of 3D objects based on VTK.

- [VisPy](https://vispy.org/) - High-performance scientific visualization based on OpenGL.

- [vtk](https://www.vtk.org/) - 3D computer graphics, image processing, and visualization that includes a Python interface.



## Geospatial



**[`^        back to top        ^`](#table-of-contents)**



- [cartopy](https://github.com/SciTools/cartopy) - A cartographic python library with matplotlib support.

- [GeoVista](https://github.com/bjlittle/geovista) - Cartographic rendering and mesh analytics powered by PyVista.



## Graphs and networks



**[`^        back to top        ^`](#table-of-contents)**



- [pygraphviz](https://pypi.org/project/pygraphviz/) - Python interface to [Graphviz](http://www.graphviz.org/).



## Other domain-specific



**[`^        back to top        ^`](#table-of-contents)**



- [missingno](https://github.com/ResidentMario/missingno) - provides flexible toolset of data-visualization utilities that allows quick visual summary of the completeness of your dataset, based on matplotlib.



## Large-data rendering



**[`^        back to top        ^`](#table-of-contents)**



## Dashboarding



**[`^        back to top        ^`](#table-of-contents)**



- [dash](https://plot.ly/products/dash/) - Built on top of Flask, React and Plotly aimed at analytical web applications.

  - [awesome-dash](https://github.com/Acrotrend/awesome-dash)

- [Streamlit](https://streamlit.io/) - Streamlit turns data scripts into shareable web apps in minutes. All in pure Python. No front‑end experience required.



## Colormapping



**[`^        back to top        ^`](#table-of-contents)**



## Not in PyViz



**[`^        back to top        ^`](#table-of-contents)**



- [diagram](https://github.com/tehmaze/diagram) - Text mode diagrams using UTF-8 characters

- [diagrams](https://github.com/mingrammer/diagrams) - Diagram as Code.

- [ggplot](https://github.com/yhat/ggpy) - plotting system based on [R's](#r-tools) ggplot2.

- [ipychart](https://github.com/nicohlr/ipychart) - The power of Chart.js in Jupyter Notebook.

- [pandas-profiling](https://github.com/pandas-profiling/pandas-profiling) - generates statistical analytic reports with visualization for quick data analysis.

- [pptk](https://github.com/heremaps/pptk) - Visualize and work with 2D/3D pointclouds

- [pyechars](https://github.com/pyecharts/pyecharts) - Python binding for Echarts library.

- [three.py](https://github.com/stemkoski/three.py/) - Easy to use 3D library based on PyOpenGL. Inspired by Three.js.

- [veusz](https://veusz.github.io/) - Python multiplatform GUI plotting tool and graphing library